heritability estimation for binary and quantitative traits

From: mahboob_alam <asremlforum_at_VSNI.CO.UK>
Date: Wed, 22 Jul 2009 10:12:45 +0100

Dear Sir,
This is Mahboob Alam, from Yeungnam university , Korea. I am doing research on a Korean native dog development. Very recently I have come close to ASREML and trying to analyze my data for heritability estimation for physical and behavioral traits.
The data file includes animals, parents and measurements where there is no specification on full sib or half sib families. Some animals appeared as parents in the next generation but not all. I donā€™t have any missing value for fixed factors or dependent variables but missing some parents. I have done a very simple analysis(univariate) as a first time try according to the ASREML manual.

In this regard, I have attached two data files, one for quantitative trait and another is for qualitative trait. and thereby I have attached my result files also.
Frankly speaking, I am really confused about my next steps:
1. Firstly, I will really be very glad if I am assured that my *.as and *.pin files are right on track. i.e. for heritability estimation my codes are right in terms of the variance components I got in *.asr file and are specified in the *.pin file.
2. Secondly, I have used those factors and their interactions in the model for quantitative trait (body weight) which were shown as highly significant ( sex [p<0.0001], birth_year [p<0.0001], test_age[p<0.0001], sex*test_age [p<0.01] using SAS proc glm procedure.
- In this case if I use all this factors I get 7 singularities in the design matrix.
- In contrast, if I exclude the interaction (sex*test_age) which is also significant, then, I get only 3 singularities cases. So, I am really confused that which model I should choose.

[ Actually, how much this differences in singularities may play a role in the model output specially when I am getting the convergence in every case. I mean, how can I deal the situation like this for inclusion or exclusion of factors /interactions? In that case the factor was significant. If you give a suggestion on my query that will be really appreciable]

3. Thirdly, for the binary analysis , I used !BIN !LOGIT. In this regard, I would like to request you to take a glance on my *.asr, *.pin file for the correctness.
- I used a conversion factor of 3.29 in the pin file for the variance part I got in *.asr file.
-Do you think that this has been done correctly plotted for the right variance component ? Moreover, can I draw any valid conclusion on heritability estimates, for a qualitative trait based on binary analysis, specially from my analysis codes?

Your every steps towards me will be really enjoyable !
Looking forward...
[Note: I have provided the complete data files exactly same as mine which I used for all derivations attached here]

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Received on Thu Jul 22 2009 - 10:12:45 EST

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